Results (PhD Chapter 2)


This series of files compile all analyses done during Chapter 2:

All analyses have been done with R 3.6.0.

Click on the table of contents in the left margin to assess a specific analysis
Click on a figure to zoom it

To assess Section 2, click here.
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Human activities considered for the analyses:

Data is also available for the number of captured individuals for dogwhelk (Buccinum sp.), common crab (Cancer irroratus), snowcrab (Chinoecetes opilio), nordic shrimp (Pandalus borealis), arctic surfclam (Mactromeris polynyma) and american lobster (Homarus americanus) fisheries.


1. Maps

1.1. General map

1.2. Parameters maps

Depth

Isobaths

2. Modelling of non-fisheries human activities influence (WIP)

The influence of each human activity has been modelled at each station, in order to be later used in prediction models (see section 2).

We calculated an index of influence for each activity \(I_{ij}\). The weighting parameter \(w_{j}\) is specific for each activity.

\[ I_{ij} = w_{j} . P_{ij} \]

For non-fisheries activities, the probability of influence \(P_{ij}\) has been calculated based on the distance from the source(s), bathymetry and hydrodynamics influences.

\[ P_{ij} = f_{j} \left( D_{ij}, \Delta Z_{ij}, H_{i} \right) \]

  • \(i\) is a station
  • \(j\) is a human activity
  • \(f_{j}\) is the decay function of activity \(j\)
  • \(D_{ij}\) is the distance of station \(i\) from the source of activity \(j\)
  • \(\Delta Z_{ij}\) is the bathymetry index at station \(i\) for activity \(j\)
  • \(H_{i}\) is the hydrodynamic index at station \(i\)

2.1. Distance form the source and decay function

This corresponds to \(D_{ij}\) and \(f_{j}\) in Formula 2.

First, we need to calculate the distance of each station from the source(s) of the activity. This proxy will allow to take coasts and island into consideration (necessary at BSI), and will then be used to calculated the probabilities of influence. Distances are in meters and were computed with the package gdistance.

Second, each human activity has its own decay function \(f_{j}\). A careful literature review will be needed to support it, as parameters and mathematical links will be decided and settled by us. The help of Frédéric Guichard may be needed! A parameter max_inf needs to be defined for each activity, beyond which the effect of an AH can be neglected.

The following maps present the values of \(D_{ij}\) before and after the use of the decay function \(f_{j}\). The latter will be used for the following steps.

CityInf

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 4500.

InduInf

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 4500.

DredColl

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 1000.

DredDump

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

MoorSite

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

RainSew

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

WastSew

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

CityWha

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

InduWha

Raw distances

With the decay function

A linear decay function is used here, with parameter max_inf set to 3000.

2.2. Bathymetry index

This corresponds to \(\Delta Z_{ij}\) in Formula 2.

This section is under discussion with Remi Daigle and Frédéric Guichard.

TO BE ADDED.

2.3. Hydrodynamic index

This corresponds to \(H_{i}\) in Formula 2.

This section is under discussion with Remi Daigle, Simon Bélanger and Frédéric Guichard.

TO BE ADDED.

2.4. Weighting parameter

This corresponds to \(w_{j}\) in Formula 1.

The following table shows the weights \(w_{j}\) for each non-fishery human activity:

CityInf InduInf DredColl DredDump MoorSite RainSew WastSew CityWha InduWha
1 1 1 1 1 1 1 1 1

2.5. Index of influence

This corresponds to \(I_{ij}\) in Formula 1.

Finally, we can calculate \(P_{ij}\) and use \(w_{j}\) in order to calculate \(I_{ij}\).

TO BE ADDED.

CityInf

InduInf

DredDump

DredDump

MoorSite

RainSew

WastSew

CityWha

InduWha

3. Modelling of fisheries human activities influence (WIP)

The influence of each human activity has been modelled at each station, in order to be later used in prediction models (see section 2).

We calculated an index of influence for each activity \(I_{ij}\). The weighting parameter \(w_{j}\) is specific for each activity.

\[ I_{ij} = w_{j} . P_{ij} \]

\(P_{ij}\) for fisheries activities have been calculated thanks to David Beauchesne’s Saint-Lawrence Database, according to the intensity of the gears deployed.

3.1. Probability of influence

This corresponds to \(P_{ij}\) in Formula 3.

TO BE ADDED.

3.2. Weighting parameter

This corresponds to \(w_{j}\) in Formula 3.

The following table shows the weights \(w_{j}\) for each fishery:

FishTrap FishTraw FishLine FishNet FishDred
1 1 1 1 1

3.3. Index of influence

This corresponds to \(I_{ij}\) in Formula 3.

We can then combine \(P_{ij}\) and \(w_{j}\) to calculate \(I_{ij}\).

TO BE ADDED.


Elliot Dreujou

2019-10-07